4/22/2019 Exosome Analysis

library(tidyverse)

Registered S3 method overwritten by 'dplyr':
  method           from
  print.rowwise_df     
── Attaching packages ─────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
✔ ggplot2 3.2.0     ✔ purrr   0.3.2
✔ tibble  2.1.3     ✔ dplyr   0.8.3
✔ tidyr   0.8.3     ✔ stringr 1.4.0
✔ readr   1.3.1     ✔ forcats 0.4.0
── Conflicts ────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

library(tidyNano)
library(themesoo)

data <- nanocombine() %>% 
  nanotidy(sep_var = c("Status","Exo_type","Dilution","Tech_rep"))

Detected the following files /Users/sean/Library/Mobile Documents/com~apple~CloudDocs/Experiments/PKH26/2019-04-22_Prok_Pexo_quantification//GD14_Pexo_1000_-ExperimentSummary.csvDetected the following files /Users/sean/Library/Mobile Documents/com~apple~CloudDocs/Experiments/PKH26/2019-04-22_Prok_Pexo_quantification//NP_plasmaExo_1000_-ExperimentSummary.csv
NTA version: 3.2
Sample name: 
Number of parameters detected: 1
Dilution factor detected: 1
Auto name = FALSE
Custom name: NULL
Dilution value: 1 (Didn't parse)
NTA version: 3.2
Sample name: 
Number of parameters detected: 1
Dilution factor detected: 1
Auto name = FALSE
Custom name: NULL
Dilution value: 1 (Didn't parse)

data

data %>%
  ggplot(aes(particle_size, True_count,
             color = Tech_rep)) +
  geom_line(size = 1) +
  facet_wrap(~Status) +
  theme_soo()

P_NP_plasma_plot <- data %>% 
  nanolyze(particle_size,Status,Exo_type,
           name = "Tech_rep",
           param_var = True_count) %>% 
  ggplot(aes(particle_size,Tech_rep_mean, color = Status)) +
  geom_line(size = 1) +
  theme_soo()

P_NP_plasma_plot %>% 
  plotly::ggplotly()

rr data %>% nanocount(Status, Exo_type,Tech_rep, param_var = True_count) %>% ungroup() %>% nanolyze(Status,Exo_type, param_var = Particle_count) %>% mutate( Sci_part_count = formatC(Param_mean, format = , digits = 2), half = formatC(Param_mean/2, format = , digits = 2)) r NA

fig02_GD14_pEV_Nanosight_plot <- data %>% 
  filter(Status == "GD14",
         particle_size < 751) %>% 
  mutate(Status = str_replace_all(Status, "GD14", "GD14.5 "),
         Samp_source = str_replace_all(Exo_type, "Pexo", "GD14.5 Placental Explant Cultured EVs")) %>%  
  nanolyze(particle_size, Status, Samp_source, param_var = True_count) %>% 
  ggplot(aes(particle_size, Param_mean, color = Status)) +
        geom_ribbon(aes(ymin = Param_mean - Param_se, 
                        ymax = Param_mean + Param_se), alpha=0.1) +
        geom_line(size = 1, alpha = 0.8) +
  scale_x_continuous(breaks = seq(0,700,100)) +
  scale_y_continuous(breaks = seq(0,1.2E10,3E9)) +
  facet_wrap(~Samp_source) +
  labs(x = "Particle size (nm)",
       y = "Concentration (particles/ml)\n") +
  scale_color_manual(values = c("#6B7CA3")) +
  themesoo::theme_soo(facet_fill = "#cccccc",
                      axis_title_size = 8,
                      axis_tick_size = 8) +
  guides(color = FALSE)


fig02_GD14_pEV_Nanosight_plot

# ggsave(plot = fig02_GD14_pEV_Nanosight_plot, "fig02_GD14_pEV_Nanosight_plot.png",
#        units = "in", width = 4, height = 2.5, dpi = 600)